Articles | Volume 24, issue 8
Hydrol. Earth Syst. Sci., 24, 3967–3982, 2020
Hydrol. Earth Syst. Sci., 24, 3967–3982, 2020

Research article 12 Aug 2020

Research article | 12 Aug 2020

Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach

Manuela I. Brunner and Eric Gilleland

Related authors

Lessons from the 2018–2019 European droughts: A collective need for unifying drought risk management
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Ksenija Cindrić Kalin, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Silvana Stevkova, Lena M. Tallaksen, Iryna Trofimova, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci. Discuss.,,, 2021
Preprint under review for NHESS
Short summary
Extreme floods in Europe: going beyond observations using reforecast ensemble pooling
Manuela I. Brunner and Louise Slater
Hydrol. Earth Syst. Sci. Discuss.,,, 2021
Revised manuscript under review for HESS
Short summary
A space-time Bayesian hierarchical modeling framework for projection of seasonal streamflow extremes
Álvaro Ossandón, Manuela I Brunner, Balaji Rajagopalan, and William Kleiber
Hydrol. Earth Syst. Sci. Discuss.,,, 2021
Revised manuscript accepted for HESS
Short summary
Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634,,, 2021
Short summary
Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119,,, 2021
Short summary

Related subject area

Subject: Engineering Hydrology | Techniques and Approaches: Stochastic approaches
Identifying sensitivities in flood frequency analyses using a stochastic hydrologic modeling system
Andrew J. Newman, Amanda G. Stone, Manabendra Saharia, Kathleen D. Holman, Nans Addor, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 5603–5621,,, 2021
Short summary
Characteristics and process controls of statistical flood moments in Europe – a data-based analysis
David Lun, Alberto Viglione, Miriam Bertola, Jürgen Komma, Juraj Parajka, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 5535–5560,,, 2021
Short summary
Objective functions for information-theoretical monitoring network design: what is “optimal”?
Hossein Foroozand and Steven V. Weijs
Hydrol. Earth Syst. Sci., 25, 831–850,,, 2021
Short summary
Numerical investigation on the power of parametric and nonparametric tests for trend detection in annual maximum series
Vincenzo Totaro, Andrea Gioia, and Vito Iacobellis
Hydrol. Earth Syst. Sci., 24, 473–488,,, 2020
Short summary
Spatially dependent flood probabilities to support the design of civil infrastructure systems
Phuong Dong Le, Michael Leonard, and Seth Westra
Hydrol. Earth Syst. Sci., 23, 4851–4867,,, 2019
Short summary

Cited articles

Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: Catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sc., 21, 5293–5313,, 2017. a
Blum, A. G., Archfield, S. A., and Vogel, R. M.: On the probability distribution of daily streamflow in the United States, Hydrol. Earth Syst. Sci., 21, 3093–3103,, 2017. a, b
Bracken, C., Rajagopalan, B., Cheng, L., Kleiber, W., and Gangopadhyay, S.: Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain, Water Resour. Res., 52, 6643–6655,, 2016. a
Breakspear, M., Brammer, M., and Robinson, P. A.: Construction of multivariate surrogate sets from nonlinear data using the wavelet transform, Physica D, 182, 1–22,, 2003. a, b, c
Brunner, M. I. and Furrer, R.: PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization, available at: (last access: 28 May 2020), 2019. a, b
Short summary
Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but yet unobserved streamflow time series with the same characteristics as the observed data. We propose a stochastic simulation approach in the frequency domain instead of the time domain. Our evaluation results suggest that the flexible, continuous simulation approach is valuable for a diverse range of water management applications.